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Linus Torvalds used AI to fix a Linux bug, and now LLM critics on Linux face an uncomfortable choice (www.xda-developers.com)
submitted 6 days ago by to c/technology@lemmy.world
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https://lists.debian.org/debian-project/2026/08/msg00041.html

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[+] -9 points 5 days ago (1 child)

If you don't have anything better to say than an ad hominem fallacy and a red herring fallacy, then you're totally discrediting yourself.

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  • [–] 8 points 5 days ago (1 child)

    Yes, because your original comment was so thought out and well reasoned to begin with 🙄

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  • [–] 1 point 5 days ago (2 children)

    Well, it's not that I'm telling another thing than the truth.

    You're attacking something totally unrelated and that I've never mentioned ("Linux 2.0") because you simply can't deny that LLM are bug-making machinegunss.

    Literature on that in my response.

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  • [–] 1 point 4 days ago

    Do you think anybody, especially Linus, is unaware that LLMs produce bugs if left to themselves? He's made it clear that PRs will continue to be judged on their code quality as they have all this while. Your comment is especially ironic considering how the post is about an elusive bug that took 1 line to fix, but hours upon hours and 24 other patches to debug. Anybody with any knowledge of Linus would find the idea hilarious that he'd allow, let alone commit, crappy code into the kernel. The only real issue up for debate is the ethics of it, considering the provenance of most training data, and potentially copyright issues.

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  • [–] -1 points 5 days ago* (1 child)

    Part 1:

    Code Quality (defects, bugs, logic)

    Security & Vulnerabilities

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  • [–] 0 points 5 days ago

    Part 2:

    Productivity Illusion (perception vs reality)

    Churn, Replacement & Survival

    Production Impact & Outages

    Deskilling

    • Brains show less activity when completing tasks with LLMs compared to completing tasks with search or completing tasks without digital help.
    • Developers who use early-2025 LLMs reported higher subjective performance, but were measured to have lower objective performance. This gap between subjective and objective performance was considered notable.
    • In an Anthropic study, learners using LLMs demonstrated lower learning rates on average compared to learners not using LLMs.
    • A recent study uses the term "cognitive surrender" to describe the way humans tend to offload key critical thinking skills onto LLMs, even when the output is wrong.
    • A paper entitled "AI Assistance Reduces Persistence and Hurts Independent Performance" from April 2026 by academics from MIT, Oxford, UCLA, and Carnegie Mellon showed alarming evidence that performing a variety of tasks with the help of AI for only 10 minutes causes "inpaired unassisted performance and reduced persistence". The researchers noted that "although AI assistance improves performance in the short-term, people perform significantly worse without AI and are more likely to give up"; they also pointed out that "these findings are particularly concerning because persistence is foundational to skill acquisition and is one of the strongest predictors of long-term learning".
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